Abstract

Mammographic breast density (MBD) is a strong independent risk factor for breast cancer (BC). We designed a matched case–case study in the EPIC Florence cohort, to evaluate possible associations between the pre-diagnostic metabolomic profile and the risk of BC in high- versus low-MBD women who developed BC during the follow-up. A case–case design with 100 low-MBD (MBD ≤ 25%) and 100 high-MDB BC cases (MBD > 50%) was performed. Matching variables included age, year and type of mammographic examination. 1H NMR metabolomic spectra were available for 87 complete case–case sets. The conditional logistic analyses showed an inverse association between serum levels of alanine, leucine, tyrosine, valine, lactic acid, pyruvic acid, triglycerides lipid main fraction and 11 VLDL lipid subfractions and high-MBD cases. Acetic acid was directly associated with high-MBD cases. In models adjusted for confounding variables, tyrosine remained inversely associated with high-MBD cases while 3 VLDL subfractions of free cholesterol emerged as directly associated with high-MBD cases. A pathway analysis showed that the “phenylalanine, tyrosine and tryptophan pathway” emerged and persisted after applying the FDR procedure. The supervised OPLS-DA analysis revealed a slight but significant separation between high- and low-MBD cases. This case–case study suggested a possible role for pre-diagnostic levels of tyrosine in modulating the risk of BC in high- versus low-MBD women. Moreover, some differences emerged in the pre-diagnostic concentration of other metabolites as well in the metabolomic fingerprints among the two groups of patients.

Highlights

  • Mammographic breast density (MBD) is a strong independent risk factor for breast cancer (BC)

  • This study aimed to evaluate the possible differential role of individual pre-diagnostic metabolomic profiles in two matched series of BC cases identified in participants with low or high MBD

  • Pre-diagnostic serum samples from BC cases were examined in the frame of a case–case study nested in the European Prospective Investigation into Cancer and nutrition (EPIC) Florence cohort

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Summary

Introduction

Mammographic breast density (MBD) is a strong independent risk factor for breast cancer (BC). We designed a matched case–case study in the EPIC Florence cohort, to evaluate possible associations between the pre-diagnostic metabolomic profile and the risk of BC in high- versus low-MBD women who developed BC during the follow-up. The supervised OPLS-DA analysis revealed a slight but significant separation between high- and low-MBD cases. This case–case study suggested a possible role for pre-diagnostic levels of tyrosine in modulating the risk of BC in high- versus low-MBD women. Mammographic breast density (MBD) extensively emerged as a strong risk factor for breast cancer (BC), regardless of any potential masking effect. Nuclear Magnetic Resonance spectroscopy (NMR) is suitable for the high-throughput, untargeted, metabolomics analysis of serum s­ amples[22] and provides a comprehensive picture of all metabolites present in the sample above the NMR detection limit (1 μM)[23]

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